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A Three-layer MRF model for Object Motion Detection in Airborne Images

Csaba Benedek 1 Tamás Szirányi 1 Zoltan Kato 1 Josiane Zerubia 1
1 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : In this report, we give a probabilistic model for automatic change detection on airborne images taken with moving cameras. To ensure robustness, we adopt an unsupervised coarse matching instead of a precise image registration. The challenge of the proposed model is to eliminate the registration errors, noise and the parallax artifacts caused by the static objects having considerable height (buildings, trees, walls etc.) from the difference image. We describe the background membership of a given image point through two different features, and introduce a novel three-layer Markov Random Field (MRF) model to ensure connected homogenous regions in the segmented image.
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Submitted on : Monday, June 4, 2007 - 10:19:33 AM
Last modification on : Friday, February 4, 2022 - 3:19:31 AM
Long-term archiving on: : Friday, November 25, 2016 - 4:12:52 PM


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  • HAL Id : inria-00150805, version 2



Csaba Benedek, Tamás Szirányi, Zoltan Kato, Josiane Zerubia. A Three-layer MRF model for Object Motion Detection in Airborne Images. [Research Report] RR-6208, INRIA. 2007, pp.35. ⟨inria-00150805v2⟩



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